Real-time hybrid controls of energy storage and load shedding for integrated power and energy systems of ships

被引:3
|
作者
Vu, Linh [1 ]
Nguyen, Thai-Thanh [2 ]
Nguyen, Bang Le-Huy [3 ]
Anam, Md. Isfakul [1 ]
Vu, Tuyen [1 ]
机构
[1] Clarkson Univ, Potsdam, Germany
[2] New York Power Author NYPA, Adv Grid Innovat Lab Energy AGILe, New York, NY USA
[3] Los Alamos Natl Lab, Los Alamos, NM USA
关键词
Energy management; Ship power system; Resilience; Load shedding; Energy storage system; Receding horizon optimization; SHIPBOARD POWER; PREDICTIVE CONTROL; OPTIMIZATION METHOD; MANAGEMENT; PERFORMANCE; STRATEGY; FLUCTUATIONS; OPERATION;
D O I
10.1016/j.epsr.2024.110191
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp -rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state -of -charge (SoC) of ESS and prioritizes the SCESS's SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real -time EMS implementation. A comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance.
引用
收藏
页数:12
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